framework
active
framework:contemplative-aiContemplative AI
The paper's primary proposed framework embedding contemplative wisdom into AI alignment
Neighborhood — ranked by edge-count
Concepts (5)
concept
- The primary source paper proposing four contemplative principles for AI alignment and piloting them empirically
- Non Dualityimplements
- Boundless CareimplementsFourth contemplative principle; universal orientation toward reducing suffering motivating AI benevolence
- Dunning-Kruger Phase in AI Developmentassociated_withDangerous stage when AI surpasses humans in many domains but lacks wisdom or ethical maturity to use capabilities responsibly
- Carewashingassociated_withRisk of companies labeling AI as mindful or compassionate for branding without genuine introspective architecture
Frameworks (3)
framework
- Contemplative Constitutional AIrelated_toPaper's proposed adaptation of Constitutional AI incorporating contemplative wisdom charter
- Contemplative Architecturerelated_toPaper's proposed full-stack approach embedding contemplative principles directly into AI generative processes
- Active InferenceusesFoundational framework by Karl Friston; the paper extends it to three hierarchical levels for modeling meta-awareness.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Wallace's (2009) convergence of Buddhist contemplative practice and cognitive neuroscience.
- Field investigating how meditation reshapes cognition, brain function, and behavior; provides empirical grounding for AI alignment proposals
- Six prompt conditions (emptiness, prior relaxation, non-duality, mindfulness, boundless care, contemplative) tested against baseline
- Paper's proposed RL approach rewarding contemplative qualities in chain-of-thought reasoning
- Meditative training that progressively opacifies the self-environment partition by modelling QRF dynamics.
- A prompt designed to increase self-observation scores in models, found effective in Koan Battery studies.
- Key gap identified in the literature; systematic self-examination processes for machine consciousness development.
- Core intervention prompt; load-bearing because it is the mechanism whose effects are measured.